Integrating multidimensional genomic data to discover clinically-relevant predictive models-Alzheimer's Supplement
整合多维基因组数据以发现临床相关的预测模型-阿尔茨海默氏症补充品
基本信息
- 批准号:10286414
- 负责人:
- 金额:$ 21.4万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-04-12 至 2023-03-31
- 项目状态:已结题
- 来源:
- 关键词:3xTg-AD mouseAdministrative SupplementAgeAgingAlzheimer&aposs DiseaseAlzheimer&aposs disease modelAlzheimer&aposs disease related dementiaAlzheimer’s disease biomarkerAneuploidyAnimal Disease ModelsApplications GrantsAwardBiologicalBiological MarkersBloodBrainCancer ScienceChromosomal InstabilityChromosomesCollaborationsConsensusCopy Number PolymorphismCpG Island Methylator PhenotypeDNADNA MethylationDataData AnalysesData ScienceData SetDeteriorationDiseaseEtiologyFutureGenomic InstabilityGenotypeGeroscienceGoalsHippocampus (Brain)HumanInterdisciplinary StudyKnowledgeLinkMaintenanceMalignant NeoplasmsMeasuresMethodologyMethodsMethylationMusMuscleNational Human Genome Research InstituteOrganParentsPathogenesisPeripheralPlasmaPositioning AttributePrecision therapeuticsResearchRisk FactorsRoleSentinelStructureTechnologyTestingTherapeuticWorkbasebrain tissuecirculating biomarkersclinically relevantdensitydesigndrug repurposingearly detection biomarkersgenome sciencesgenomic datahuman diseaseneuron developmentparent projectpredictive modelingpromoterresponsesextargeted biomarkertibialis anterior muscletool
项目摘要
Genomic instability (GIN) is a primary hallmark of aging, which is the greatest known risk factor for both
Alzheimer’s disease (AD) and cancer. Because there is no consensus on which measures of GIN are most
biologically and clinically relevant, in our parent project we are testing GIN metrics and developing tools for
assessing GINs reproducibly across cancer. Our approaches are designed to be technology-, platform-, and
disease-agnostic and therefore should also apply to AD. Our focus, thus far, has been on chromosomal
instability (CIN, altered chromosome number and structure; e.g., total number of breakpoints, percent of bases
with copy number variation, total functional aneuploidy, etc.) and DNA methylation instabilities (DNAm, e.g.,
CpG island methylator phenotype; CIMP, widespread altered promoter methylation, density of methylated to
non-methylated CpGs, etc.). In cancer we and others have shown GIN is linked to disease etiology and
progression, response to therapeutics, and is a potential disease biomarker. While AD animal models confirm
DNA integrity impacts neuronal development, function, and maintenance and human aging studies further
implicate a role for GIN in brain deterioration, GIN’s role in AD is not clear. There is a critical need to evaluate
AD-specific GIN, particularly as potential precision therapy targets and early biomarkers defining therapeutic
windows. Our interdisciplinary research team has AD, aging, genomic instability, cancer, genomics, and data
science expertise and is well positioned to undertake these studies. Our long term research goal is to
understand the role of GIN in the context of aging for multiple conditions and how GIN further contributes to
disease etiology, progression, and treatment. Here, we propose the first steps towards demonstrating utility of
our methodology in additional diseases by applying them to publicly available AD human and mouse data and
comparing the resulting GIN profiles to cancer data analyses in our parent award. We hypothesize this will
determine the extent and type of CIN (Aim 1) and DNAm instability (Aim 2) in AD. Critically, we will
demonstrate how generalizable our methods and gained knowledge are, add AD examples and vignettes to
the tools we are developing, and compare GINs across diseases (AD and cancers), species (human and
mouse), and with respect to sex and age. Additionally, we will generate genotype and DNAm data from
3xTG-AD mouse hippocampus (AD-relevant brain tissue), tibialis anterior muscle (as a sentinel organ), and
plasma (as a circulating factor) to investigate GIN as an AD biomarker. Critically, with this supplement we will
demonstrate generalizability of the parent award methods and knowledge by expanding our existing non-AD
NHGRI award to have an AD focus. This work will also stimulate additional activity and collaborations in AD
and related dementias by providing preliminary data for several future grant proposals targeting the role of GIN
in aging as a general disease mechanism, in AD pathogenesis, for drug repurposing and shared etiology
studies between cancer and AD, and with respect to the utility of GINs as peripheral or circulating biomarkers.
基因组不稳定性(GIN)是衰老的主要标志,这是两者的最大已知风险因素
阿尔茨海默氏病(AD)和癌症。因为尚无共识,杜松子酒的度量最多
在生物学和临床上相关的是,在我们的父项目中,我们正在测试杜松子酒指标和开发工具
在癌症中可重复地评估杜松子酒。我们的方法被设计为技术,平台和
疾病敏捷,因此也应适用于AD。到目前为止,我们的重点一直放在染色体上
不稳定性(CIN,变化的染色体数和结构;例如,断点总数,基础百分比
随着拷贝数的变化,总功能性非整倍性等)和DNA甲基化不稳定性(例如DNAM,例如,
CpG岛甲基表型; CIMP,宽度改变了启动子甲基化,甲基化的密度
非甲基化的CPG等)。在癌症中,我们和其他人表明杜松子酒与疾病的病因学和
进展,对治疗的反应,是一种潜在的疾病生物标志物。广告动物模型确认
DNA完整性会进一步影响神经元的发展,功能和维持和人类衰老研究
在大脑定义中实施杜松子酒的作用,杜松子酒在AD中的作用尚不清楚。评估迫切需要
广告特异性杜松
视窗。我们的跨学科研究团队拥有广告,衰老,基因组不稳定性,癌症,基因组学和数据
科学专业知识,可以很好地进行这些研究。我们的长期研究目标是
了解杜松子酒在多种疾病的衰老中的作用,以及杜松子酒如何进一步贡献
疾病的病因,进展和治疗。在这里,我们提出了证明实用性的第一步
我们在其他疾病中的方法将其应用于公开可用的AD人类和鼠标数据以及
将最终的杜松子酒概况与我们父母奖中的癌症数据分析进行比较。我们假设这将
确定AD中CIN的程度和类型(AIM 1)和DNAM不稳定性(AIM 2)。至关重要的是,我们会的
证明我们的方法和获得知识的推广程度,将广告示例和小插曲添加到
我们正在开发的工具,并比较跨疾病(广告和癌症),物种(人类和人类)的杜松子酒
鼠标),关于性别和年龄。此外,我们将从
3XTG-AD小鼠海马(与AD相关的脑组织),胫骨前肌(作为前哨器官)和
血浆(作为循环因子)以AD生物标志物研究杜松子酒。至关重要的是,有了这种补充,我们将
通过扩展我们现有的非AD,证明父母奖励方法和知识的普遍性
NHGRI奖将成为广告重点。这项工作还将刺激广告中的其他活动和合作
和相关的痴呆症,通过提供针对杜松子酒作用的几项未来赠款建议的初步数据
在衰老作为一种一般疾病机制中,在AD发病机理中,用于药物重新利用和共同病因
癌症和AD之间的研究以及杜松子作为周围或循环生物标志物的实用性。
项目成果
期刊论文数量(9)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Nucleic acid liquid biopsies in Alzheimer's disease: current state, challenges, and opportunities.
- DOI:10.1016/j.heliyon.2022.e09239
- 发表时间:2022-04
- 期刊:
- 影响因子:4
- 作者:Soelter, Tabea M.;Whitlock, Jordan H.;Williams, Avery S.;Hardigan, Andrew A.;Lasseigne, Brittany N.
- 通讯作者:Lasseigne, Brittany N.
Evaluating cancer cell line and patient-derived xenograft recapitulation of tumor and non-diseased tissue gene expression profiles in silico.
评估癌细胞系和患者来源的异种移植物在计算机中再现肿瘤和非患病组织基因表达谱。
- DOI:10.1101/2023.04.11.536431
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Williams,AveryS;Wilk,ElizabethJ;Fisher,JenniferL;Lasseigne,BrittanyN
- 通讯作者:Lasseigne,BrittanyN
Inferring chromosomal instability from copy number aberrations as a measure of chromosomal instability across human cancers.
从拷贝数畸变推断染色体不稳定性作为人类癌症染色体不稳定性的衡量标准。
- DOI:10.1101/2023.05.24.542174
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Taluri,Sasha;Oza,VishalH;Soelter,TabeaM;Fisher,JenniferL;Lasseigne,BrittanyN
- 通讯作者:Lasseigne,BrittanyN
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Brittany Nicole Lasseigne其他文献
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{{ truncateString('Brittany Nicole Lasseigne', 18)}}的其他基金
Integrating multidimensional genomic data to discover clinically-relevant predictive models
整合多维基因组数据以发现临床相关的预测模型
- 批准号:
9901758 - 财政年份:2019
- 资助金额:
$ 21.4万 - 项目类别:
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